Intel Graphics 24EU Mobile vs NVIDIA RTX 3500 Embedded Ada Generation Comparison

FAQ

Q: What are the core specifications of the Intel Graphics 24EU Mobile?

A: The Intel Graphics 24EU Mobile is an integrated GPU based on the Xe-LP architecture, built on a 10 nm process at Intel's foundry. It features 192 shading units, 12 texture mapping units, and 4 raster output pipelines. Its base clock is 300 MHz with a boost clock of 1000 MHz, and it relies on system shared memory for both capacity and bandwidth, making its memory performance system dependent.

Q: What are the key specifications of the NVIDIA RTX 3500 Embedded Ada Generation?

A: The NVIDIA RTX 3500 Embedded Ada Generation is a discrete GPU based on the Ada Lovelace architecture, built on a 5 nm process at TSMC. It uses the AD104 chip with 35,800 million transistors on a 294 mm² die. It has 5120 shading units, 160 TMUs, 64 ROPs, 40 RT cores, and 160 tensor cores. The GPU operates at a base clock of 1725 MHz and a boost clock of 2250 MHz, paired with 12 GB of GDDR6 memory on a 192-bit bus, delivering 432.0 GB/s of bandwidth.

Q: How do the power requirements compare between these two GPUs?

A: The Intel Graphics 24EU Mobile has a TDP of 6 W and uses a Ring Bus interface, drawing power from the host system. The NVIDIA RTX 3500 Embedded Ada Generation has a TDP of 100 W, requires no external power connectors, and has a suggested PSU rating of 300 W. The data shows a substantial difference, with the NVIDIA part consuming over 16 times the power budget of the Intel integrated solution.

Q: What are the API support differences between the two?

A: Both GPUs support OpenGL 4.6 and Vulkan 1.4. The key difference lies in DirectX support: the Intel Graphics 24EU Mobile supports DirectX 12 (12_1), while the NVIDIA RTX 3500 Embedded Ada Generation supports DirectX 12 Ultimate (12_2), which includes additional features such as hardware ray tracing and mesh shaders.

Q: How do the compute throughput figures differ?

A: The NVIDIA RTX 3500 Embedded Ada Generation delivers 23.04 TFLOPS of FP32 compute and 23.04 TFLOPS of FP16 compute with a 1:1 ratio. The Intel Graphics 24EU Mobile provides 384.0 GFLOPS of FP32 and 768.0 GFLOPS of FP16 with a 2:1 ratio. This indicates the NVIDIA part has roughly 60 times the FP32 throughput of the Intel integrated GPU.

Q: What are the release timelines for these products?

A: The Intel Graphics 24EU Mobile was released at the end of 2024, specifically on 2024-12-31. The NVIDIA RTX 3500 Embedded Ada Generation was released earlier, on 2023-03-20. Both products are currently listed as Active in production status.

Where Each One Wins

The benchmark data reveals a clear division of use cases based on the architectural and specification differences between these two GPUs.

The Intel Graphics 24EU Mobile wins in scenarios prioritizing minimal power consumption and system integration. With a TDP of 6 W, it is designed for ultra-portable devices where battery life and thermal constraints are paramount. Its Ring Bus interface and system shared memory architecture mean it requires no dedicated VRAM allocation, simplifying system design for thin-and-light laptops. The GPU is part of the HD Graphics-T (Twin Lake) generation, targeting basic graphical output, video playback, and light productivity tasks. Its 4.000 GPixel/s pixel rate and 12.00 GTexel/s texture rate are sufficient for rendering simple 2D interfaces and handling basic media acceleration.

The NVIDIA RTX 3500 Embedded Ada Generation wins in all performance-intensive workloads. Its 5120 shading units, 160 TMUs, and 64 ROPs provide a massive parallel processing capability. The inclusion of 40 RT cores and 160 tensor cores enables hardware-accelerated ray tracing and AI-based features such as DLSS, which the Intel part lacks entirely. The 432.0 GB/s memory bandwidth, coupled with 12 GB of dedicated GDDR6 memory, allows for large texture loads and complex scene rendering without relying on system memory. This makes the NVIDIA part suitable for professional 3D rendering, scientific computation, and advanced content creation, where its 23.04 TFLOPS FP32 throughput and 144.0 GPixel/s pixel rate deliver the necessary performance.

The percentile data shows both GPUs sit at the 50th percentile among all GPUs in the database, but this aggregate position masks the extreme performance disparity. The Intel part's 1000 MHz boost clock and 192 shading units place it in the entry-level integrated segment, while the NVIDIA part's 2250 MHz boost clock and 5120 shading units position it in the high-end mobile workstation segment. The use case split is therefore straightforward: the Intel GPU serves basic computing needs in power-constrained environments, while the NVIDIA GPU targets demanding professional applications where performance takes precedence over power efficiency.

Architecture Differences

The two GPUs employ fundamentally different architectures from different vendors, built on different process nodes. The Intel Graphics 24EU Mobile uses the Xe-LP architecture, Intel's low-power graphics architecture designed for integrated solutions. It is manufactured on a 10 nm process at Intel's own foundry. The chip, codenamed Twin Lake, belongs to the HD Graphics-T (Twin Lake) generation. The architecture implements 192 shading units organized in a configuration that prioritizes area and power efficiency over raw throughput.

The NVIDIA RTX 3500 Embedded Ada Generation uses the Ada Lovelace architecture, NVIDIA's high-performance GPU architecture. It is built on a 5 nm process at TSMC, allowing for a transistor density of 121.8 million transistors per square millimeter. The AD104 chip packs 35,800 million transistors into a 294 mm² die, representing a significantly more complex and dense design. The Ada Lovelace architecture introduces dedicated hardware for ray tracing (40 RT cores) and tensor operations (160 tensor cores), features entirely absent from the Intel Xe-LP design.

The memory architecture differs fundamentally. The Intel GPU uses system shared memory, where the GPU accesses the same memory pool as the CPU via the Ring Bus interface. This eliminates dedicated VRAM but makes bandwidth system dependent and shared with other workloads. The NVIDIA GPU uses 12 GB of dedicated GDDR6 memory on a 192-bit bus, providing an isolated 432.0 GB/s bandwidth that does not compete with CPU memory traffic. This architectural difference explains the substantial gap in memory throughput capabilities.

The feature sets diverge on API support as well. The Intel GPU supports DirectX 12 (12_1), which includes the base DirectX 12 feature set. The NVIDIA GPU supports DirectX 12 Ultimate (12_2), adding features like hardware ray tracing, variable rate shading, and mesh shaders. Both support OpenGL 4.6 and Vulkan 1.4, but the underlying hardware capabilities differ dramatically. The NVIDIA part's 160 tensor cores enable AI acceleration, while the Intel part has no equivalent hardware.

Specification Differences

The recorded data shows substantial differences across nearly every specification category between the Intel Graphics 24EU Mobile and the NVIDIA RTX 3500 Embedded Ada Generation.

The process node: Intel uses 10 nm, while NVIDIA uses 5 nm. The foundry also differs: Intel fabricates its own chip, while NVIDIA uses TSMC. The transistor count is listed as unknown for Intel, while the NVIDIA chip contains 35,800 million transistors on a 294 mm² die.

Clock speeds differ significantly. The Intel GPU has a base clock of 300 MHz and a boost clock of 1000 MHz. The NVIDIA GPU has a base clock of 1725 MHz and a boost clock of 2250 MHz. The memory clock also differs: Intel uses system shared memory, while NVIDIA operates at 2250 MHz with 18 Gbps effective speed.

Memory specifications show a complete divergence. The Intel GPU has system shared memory in terms of size, type, bus width, and bandwidth (which is system dependent). The NVIDIA GPU has 12 GB of GDDR6 memory on a 192-bit bus with a fixed 432.0 GB/s bandwidth.

Compute resources differ by an order of magnitude. The Intel GPU has 192 shading units, 12 TMUs, and 4 ROPs. The NVIDIA GPU has 5120 shading units, 160 TMUs, and 64 ROPs. The NVIDIA part also has 40 RT cores and 160 tensor cores, which the Intel part does not have at all.

Throughput figures reflect these resource differences. The Intel GPU achieves 4.000 GPixel/s pixel rate, 12.00 GTexel/s texture rate, 384.0 GFLOPS FP32, and 768.0 GFLOPS FP16. The NVIDIA GPU achieves 144.0 GPixel/s pixel rate, 360.0 GTexel/s texture rate, 23.04 TFLOPS FP32, and 23.04 TFLOPS FP16.

Power and interface specifications also differ. The Intel GPU has a 6 W TDP, uses a Ring Bus interface, and has no power connectors. The NVIDIA GPU has a 100 W TDP, uses PCIe 4.0 x16, has no power connectors, and suggests a 300 W PSU. The Intel GPU's display outputs are portable device dependent, while the NVIDIA GPU has no outputs, indicating a compute-focused embedded design.

Head-to-Head Benchmarks

While the database records no direct benchmark scores for either GPU, the specification data provides a comprehensive basis for comparative analysis. The measured figures indicate the NVIDIA RTX 3500 Embedded Ada Generation holds a decisive advantage across all performance metrics.

The most dramatic difference appears in compute throughput. The NVIDIA GPU delivers 23.04 TFLOPS of FP32 performance, compared to 384.0 GFLOPS from the Intel GPU. This represents a 60-fold advantage for the NVIDIA part in single-precision floating-point workloads. FP16 performance shows a similar gap: the NVIDIA GPU achieves 23.04 TFLOPS with a 1:1 ratio, while the Intel GPU achieves 768.0 GFLOPS with a 2:1 ratio. The NVIDIA part's FP16 capability is 30 times higher than the Intel part's, and the 1:1 ratio indicates no throughput penalty for half-precision operations.

Pixel throughput follows the same pattern. The NVIDIA GPU's 144.0 GPixel/s pixel rate is 36 times higher than the Intel GPU's 4.000 GPixel/s. Texture rate shows a 30-fold difference: 360.0 GTexel/s for NVIDIA versus 12.00 GTexel/s for Intel. These figures directly reflect the ROP and TMU counts, where the NVIDIA part has 16 times more ROPs and over 13 times more TMUs.

Memory bandwidth presents one of the most striking contrasts. The NVIDIA GPU provides a fixed 432.0 GB/s from its GDDR6 memory, while the Intel GPU's bandwidth is system dependent with no fixed figure. The 12 GB dedicated memory capacity versus system shared memory further separates the two in terms of memory-intensive workloads. The NVIDIA part's 192-bit bus width and 2250 MHz memory clock enable sustained high-bandwidth access, while the Intel part must contend with CPU memory traffic.

Clock speeds also favor the NVIDIA part. Its 1725 MHz base clock is 5.75 times higher than the Intel GPU's 300 MHz base clock, and its 2250 MHz boost clock is 2.25 times higher than the Intel GPU's 1000 MHz boost clock. Higher clocks, combined with more shading units, produce the multiplicative performance advantage observed in the throughput figures.

The power envelope shows the tradeoff. The NVIDIA GPU consumes 100 W versus 6 W for the Intel GPU, a 16.7-fold increase. The suggested PSU of 300 W for the NVIDIA part indicates the full system power requirement, while the Intel IGP draws from the host system's existing power delivery. This power disparity explains the performance gap: the NVIDIA part uses its power budget to sustain high clocks across 5120 shading units, while the Intel part operates at minimal power to fit within integrated thermal constraints.

The API support difference, while narrower, still matters. The NVIDIA GPU's DirectX 12 Ultimate (12_2) support enables hardware ray tracing via its 40 RT cores and AI acceleration via its 160 tensor cores. The Intel GPU's DirectX 12 (12_1) support lacks these hardware-accelerated features. In workloads that leverage ray tracing or tensor operations, the NVIDIA part would show an even larger relative advantage than the raw compute figures suggest, since the Intel part would need to fall back on software implementations or lack support entirely.

Both GPUs share the 50th percentile ranking in the database, but this equal percentile does not reflect equal capability. The percentile likely accounts for the different market segments these products target: the Intel IGP for basic mobile computing and the NVIDIA embedded GPU for professional mobile workstations. The data confirms that in any benchmark measuring raw graphical or compute performance, the NVIDIA RTX 3500 Embedded Ada Generation would dominate, while the Intel Graphics 24EU Mobile holds the advantage only in power efficiency and system integration simplicity.